Evidence map›Paper›PMID 25881098›Full record

ArticleBMC medical genomics2015

Progression risk assessments of individual non-invasive gastric neoplasms by genomic copy-number profile and mucin phenotype.

Diem Thi-Ngoc Vo, Takahisa Nakayama, Hiroto Yamamoto, Ken-ichi Mukaisho, Takanori Hattori, Hiroyuki Sugihara

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Diem Thi-Ngoc VoDepartment of Pathology, Division of Molecular and Diagnostic Pathology, Shiga University of Medical Science, Otsu, 520-2192, Japan. votngocdiem@gmail.com.
Takahisa NakayamaDepartment of Pathology, Division of Molecular and Diagnostic Pathology, Shiga University of Medical Science, Otsu, 520-2192, Japan. 330601@belle.shiga-med.ac.jp.
Hiroto YamamotoDepartment of Pathology, Division of Molecular and Diagnostic Pathology, Shiga University of Medical Science, Otsu, 520-2192, Japan. yamaherob00k@gmail.com.
Ken-ichi MukaishoDepartment of Pathology, Division of Molecular and Diagnostic Pathology, Shiga University of Medical Science, Otsu, 520-2192, Japan. mukaisho@googlemail.com.
Takanori HattoriDepartment of Pathology, Division of Molecular and Diagnostic Pathology, Shiga University of Medical Science, Otsu, 520-2192, Japan. hattori@belle.shiga-med.ac.jp.
Hiroyuki SugiharaDepartment of Pathology, Division of Molecular and Diagnostic Pathology, Shiga University of Medical Science, Otsu, 520-2192, Japan. sugihara@belle.shiga-med.ac.jp.
Shiga University of Medical Science · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEarly detection and treatment of non-invasive neoplasms can effectively reduce the incidence of advanced gastric carcinoma (GC), but only when the lineage is continuous between non-invasive and advanced tumours. Although a fraction of non-invasive neoplasms progress to invasive GC, it is difficult to identify individual progression-prone non-invasive neoplasms. To classify non-invasive gland-forming gastric neoplasms into clusters of different levels of progression risk, we applied mucin phenotyping and genomic DNA microarray analyses to intramucosal gland-forming gastric neoplasms.

methodsFormalin-fixed, paraffin-embedded tissues from 19 non-invasive and 24 invasive gland-forming neoplasms were obtained via endoscopic submucosal dissection or surgical excision. According to the Vienna classification, intramucosal neoplasms were classified as low-grade or high-grade non-invasive neoplasms (LGNs [category 3] and HGNs [category 4], respectively) or invasive carcinomas (intramucosal GCs and mucosal parts of submucosal or deeper GCs [category 5]). Neoplastic lesions were characterized by mucin phenotypes determined using monoclonal antibodies against MUC2, MUC5AC, MUC6, and CD10. Genomic DNA samples from mucosal neoplasms were subjected to array-based comparative genomic hybridization and subsequent unsupervised, hierarchical clustering with selected large-sized genes.

resultsThere was no significant difference in mucin phenotype between HGNs/LGNs and invasive carcinomas. The clustering classified samples into stable, unstable, and intermediate. The histological tumour grade or mucin phenotype of non-invasive neoplasms did not correlate with the clustering results. Each cluster may represent an independent lineage of different outcome because the size distribution of non-invasive tumours among the 3 clusters almost overlapped. In contrast, the unstable cluster alone included invasive carcinomas.

conclusionsThese findings suggest that the outcome of individual tumours is not stochastically determined but can be predicted from the genomic copy-number profile even at the non-invasive stage. Non-invasive neoplasms of the unstable clusters, which accounted for 21% of non-invasive neoplasms, may progress to invasive carcinomas, whereas those of stable cluster may not.

Indexed as

Gene DosageGene Expression Regulation, NeoplasticAdenocarcinomaAlgorithmsBiomarkers, TumorCell LineageCluster AnalysisComparative Genomic HybridizationDisease ProgressionGene Expression ProfilingGenome, HumanGenomicsHumansImmunohistochemistryMucinsNeoplasm InvasivenessBiomarkers, TumorMucins

Identifiers

PMID25881098
PMCPMC4346124
OpenAlexW2096660980

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.